From the 1 of 5 linked papers with an AI index.
5 papers
CLVisc Agent for autonomous relativistic hydrodynamics studies
Qi Wang, Long-Gang Pang, Shi Pu +1
The paper presents a large language model agent that can autonomously run and analyze relativistic hydrodynamic simulations of quark‑gluon plasma in heavy‑ion collisions, including…
Parton Fragmentation Functions Extracted with a Physics-Informed Neural Network
Si-Wei Dai, Fu-Peng Li, Long-Gang Pang +3
Reliable predictions of many high-energy strong interaction processes rely heavily on the non-perturbative parton fragmentation functions (FFs) extracted from existing experimental…
Impact of Initial-State Nuclear and Sub-Nucleon Structures on Ultra-Central Puzzle in Heavy Ion Collisions
Qi Wang, Long-Gang Pang, Xin-Nian Wang
Hydrodynamic models fail to describe the near-equal ratio observed in ultra-central heavy-ion collisions, despite their success in other centrality classes. This discrepa…
A Novel Deep Learning Method for Detecting Nucleon-Nucleon Correlations
Yu-Jing Huang, Zhu Meng, Long-Gang Pang +1
This study investigates the impact of nucleon-nucleon correlations on heavy-ion collisions using the hadronic transport model SMASH in GeV +$^…
Effects of Initial Nucleon-Nucleon Correlations on Light Nuclei Production in Au+Au Collisions at GeV
Qian-Ru Lin, Yu-Jing Huang, Long-Gang Pang +2
Light nuclei production in heavy-ion collisions serves as a sensitive probe of the QCD phase structure. In coalescence models, triton () and deuteron () yields depend on…